app.py

import streamlit as st
import requests
import json

# Function to call the API
def call_chatgpt_api(message, dialog_messages):
    url = "https://api.safone.dev/chatgpt"
    headers = {
        "accept": "application/json",
        "Content-Type": "application/json"
    }
    payload = {
        "message": message,
        "version": 3,
        "chat_mode": "assistant",
        "dialog_messages": dialog_messages
    }

    response = requests.post(url, headers=headers, data=json.dumps(payload))
    if response.status_code == 200:
        return response.json()
    else:
        return None

# Initialize session state if not already done
if 'dialog_messages' not in st.session_state:
    st.session_state.dialog_messages = [{"bot": "", "user": ""}]

if 'responses' not in st.session_state:
    st.session_state.responses = []

# Streamlit App
st.title('SlimshadowGPT')
st.write("This is a simple interface to interact with the GPT-3.5 API.")

# Placeholder for user input
input_placeholder = st.empty()
user_input = input_placeholder.text_input("Enter your message:")

if st.button('Send'):
    if user_input:
        st.session_state.dialog_messages.append({"bot": "", "user": user_input})
        
        with st.spinner('Generating response...'):
            response = call_chatgpt_api(user_input, st.session_state.dialog_messages)
            if response:
                assistant_message = response['choices'][0]['message']['content']
                st.session_state.dialog_messages.append({"bot": assistant_message, "user": ""})
                st.session_state.responses.append((user_input, assistant_message))
            else:
                st.write("Failed to get a response from the API.")
        
        # Clear input box after sending
        input_placeholder.text_input("Enter your message:", value="", key="user_input_clear")

# Display the conversation history
st.write("### Chat History")
for user_msg, bot_msg in st.session_state.responses:
    st.write(f"**You:** {user_msg}")
    st.write(f"**Assistant:** {bot_msg}")

# Run the app using `streamlit run app.py` in the terminal